This project aims to improve the exploitation capabilities of radar-based remote sensing techniques to measure and monitor land deformation: Differential Interferometric SAR (DInSAR) and Persistent Scatterer Interferometry (PSI). These techniques play a key role in the thematic area of Earth Sciences. They are nowadays frequently used in a wide range of applications like geology, hydrogeology, applied geology, seismology, volcanology, glaciology, landslide monitoring, ground subsidence monitoring, etc.
The importance of DInSAR and PSI has considerably grown in the last decade. A key factor is the availability of several missions that include Synthetic Aperture Radar (SAR) sensors. In particular, the launch of the Sentinel-1A and 1B missions of the Copernicus Programme caused a paradigm change: The SAR data will be available for many years from now worldwide and for free. The consolidation of such grown is represented by the creation of the Ground Motion Services (GMS). In some cases, these services are carried out at the regional scale. A European initiative started in 2016 to implement a DInSAR-based European Ground Motion Service (EGMS) to provide consistent data at a continental scale. This service is currently under development. An important part of this project is related to the exploitation of the forthcoming results of the EGMS.
Mean deformation velocity maps in the radar line-of-sight, covering a large portion of Europe (from Lanari et al. 2020).
Another fundamental factor has been the development of tools and procedures to process and analyze the DInSAR or PSI data and to increase the computational capabilities. In particular, CTTC has an in-house developed DInSAR and PSI chain. Part of this project will be devoted to the improvement of the algorithms of this chain. This part is the natural continuation of the DEMOS project, Deformation monitoring using Sentinel-1 data (Project Reference: CGL2017-83704-P).
Mean deformation velocity map over the islands of La Gomera, Tenerife and Gran Canaria, processed by the CTTC team (from Solari et al. 2017).
The main products of DInSAR and PSI are the deformation velocity and time series. The velocity map shows the linear deformation over the entire observed period. It is computed assuming a constant rate or velocity over the entire period. This product is rather robust. The deformation time series describe the deformation time history of the measurement points over the observed period. This product provides a more detailed information with respect to the previous one: it is useful to follow the deformation phenomena over time and hence to understand their kinematics and their causes. Despite its great potential, the main use of these maps has been constrained to the scientific community, due to particularities of the technique itself that can complicate the interpretation of the results. For this reason, the use of InSAR data remains very limited or non-existent among the authorities in charge of disaster management and prevention (Civil Protection in Spain) and other potential users.
Geohazard Activity Map for the Tenerife Island derived from geological-geomorphological interpretation of field and ancillary data (from Solari et al. 2017).
To facilitate the use of these data and create more friendly products and tools for non-expert users, we propose to create tools that allow the automatic analysis of large InSAR data sets to:
- Indentify the deformation signals and separate them from the noise;
- Classify these signals according to the natural or anthropic causative phenomenon;
- Estimate the areas most susceptible to experiencing ground movements in the future;
- Predict the temporal evolution of ground deformation.
References
- Lanari et al. (2020). Automatic Generation of Sentinel-1 Continental Scale DInSAR Deformation Time Series through an Extended P-SBAS Processing Pipeline in a Cloud Computing Environment. Remote Sens. 2020, 12, 2961; doi:10.3390/rs12182961.
- Solari, L., Barra, A., Herrera, G., Bianchini, S., Monserrat, O., Béjar-Pizarro, M., Crosetto, M., Sarro, R., Moretti, S. (2017). Fast detection of ground motions on vulnerable elements using Sentinel-1 InSAR data. Geomatics, Natural Hazards and Risk. DOI: 10.1080/19475705.2017.1413013.